---
title: "OMOP2OBO Dashboard"
output: 
  flexdashboard::flex_dashboard:
    storyboard: true
    source_code: embed
    orientation: columns
    vertical_layout: fill
    social: menu
---

```{r setup, include=FALSE}
library(flexdashboard)

#------------------ Parameters ------------------
# set value board colors
# https://www.w3.org/TR/css-color-3/#svg-color
cond_color <- "forestgreen"
drug_color <- "purple"
lab_color <- "#1f77b4"

# placeholder for value board counts
cond_count <- 97325
drug_count<- 10245
lab_count <- 4558

# timestamp for tables
run_time <- format(Sys.time(), "%a %b %d %X %Y")

# function for data table embedded bar charts
bar_chart <- function(label, width = "100%", height = "14px", fill = "#00bfc4", background = NULL) {
  bar <- htmltools::div(style = list(background = fill, width = width, height = height))
  chart <- htmltools::div(style = list(flexGrow = 1, marginLeft = "6px", background = background), bar)
  htmltools::div(style = list(display = "flex", alignItems = "center"), label, chart)
}


#------------------ TABLES ------------------
# create fake table data
state_names <- rownames(USArrests)
data <- USArrests 
data$States <- rownames(data)
rownames(data) <- NULL

```


Mapping Summary {data-icon="fa-map"}
===================================== 

Column { data-width=150 }
-----------------------------------------------------------------------

### conditions {.value-box}
```{r}
valueBox(value = paste(format(cond_count, big.mark = ","), "", sep = " "), 
         caption = "Conditions", 
         icon = "fas fa-procedures", 
         color = cond_color)
```

### drugs {.value-box}
```{r}
valueBox(value = paste(format(drug_count, big.mark = ","), "", sep = " "), 
         caption = "Drug Ingredients", 
         icon = "fas fa-pills", 
         color = drug_color)
```

### measurements {.value-box}
```{r}
valueBox(value = paste(format(lab_count, big.mark = ","), "", sep = " "), 
         caption = "Measurements", 
         icon = "fas fa-vials", 
         color = lab_color)
```


Column {data-width=350}
-----------------------------------------------------------------------

### Condition Mappings

```{r}
library(plotly)
library(rjson)
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
counties <- rjson::fromJSON(file=url)
url2<- "https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv"
df <- read.csv(url2, colClasses=c(fips="character"))
g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showlakes = TRUE,
  lakecolor = toRGB('white')
)
fig <- plot_ly()
fig <- fig %>% add_trace(
    type="choropleth",
    geojson=counties,
    locations=df$fips,
    z=df$unemp,
    colorscale="Viridis",
    zmin=0,
    zmax=12,
    marker=list(line=list(
      width=0)
    )
  )
fig <- fig %>% colorbar(title = "Unemployment Rate (%)")
fig <- fig %>% layout(
    title = "2016 US Unemployment by County"
)
fig <- fig %>% layout(
    geo = g
  )
fig
```


Column {data-width=350}
-----------------------------------------------------------------------

### Drug Ingredient Mappings

```{r}
library(plotly)
library(rjson)
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
counties <- rjson::fromJSON(file=url)
url2<- "https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv"
df <- read.csv(url2, colClasses=c(fips="character"))
g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showlakes = TRUE,
  lakecolor = toRGB('white')
)
fig <- plot_ly()
fig <- fig %>% add_trace(
    type="choropleth",
    geojson=counties,
    locations=df$fips,
    z=df$unemp,
    colorscale="Viridis",
    zmin=0,
    zmax=12,
    marker=list(line=list(
      width=0)
    )
  )
fig <- fig %>% colorbar(title = "Unemployment Rate (%)")
fig <- fig %>% layout(
    title = "2016 US Unemployment by County"
)
fig <- fig %>% layout(
    geo = g
  )
fig
```


Column {data-width=350}
-----------------------------------------------------------------------

### Measurement Mappings

```{r}
library(plotly)
library(rjson)
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
counties <- rjson::fromJSON(file=url)
url2<- "https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv"
df <- read.csv(url2, colClasses=c(fips="character"))
g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showlakes = TRUE,
  lakecolor = toRGB('white')
)
fig <- plot_ly()
fig <- fig %>% add_trace(
    type="choropleth",
    geojson=counties,
    locations=df$fips,
    z=df$unemp,
    colorscale="Viridis",
    zmin=0,
    zmax=12,
    marker=list(line=list(
      width=0)
    )
  )
fig <- fig %>% colorbar(title = "Unemployment Rate (%)")
fig <- fig %>% layout(
    title = "2016 US Unemployment by County"
)
fig <- fig %>% layout(
    geo = g
  )
fig
```



Data {data-icon="fa-table"}
===================================== 

### Condition Occurrence Mappings

```{r table1}

table <- reactable::reactable(
  data = data,
  pagination = FALSE,
  highlight = TRUE,
  height = 1200,
  defaultSorted = "States",
  sortable = TRUE,
  borderless = TRUE,
  defaultPageSize = nrow(data),
  columns = list(
    States = reactable::colDef(name = "States", sortable = TRUE, defaultSortOrder = "asc", align = "left"),
    Assault = reactable::colDef(name = "Assaults", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Assault), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "gold")}),
    Rape = reactable::colDef(name = "Rapes", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Rape), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "orange")}),
    Murder = reactable::colDef(name = "Murders", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Murder), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "red")})
    ))

htmltools::div(
  class = "condition-mapping-data",
  htmltools::div(class = "condition-mapping-data-header",
                 htmltools::div(
                   class = "condition-mapping-data-title",
                   "Source: OMOP2OBO v1.0 - OMOP v5.3 Condition Occurrence Mappings"),
                 paste("Last Update: ", run_time, " EST", sep = "")),
  table
)
```


### Drug Ingredient Mappings

```{r table2}

table <- reactable::reactable(
  data = data,
  pagination = FALSE,
  highlight = TRUE,
  height = 1200,
  defaultSorted = "States",
  sortable = TRUE,
  borderless = TRUE,
  defaultPageSize = nrow(data),
  columns = list(
    States = reactable::colDef(name = "States", sortable = TRUE, defaultSortOrder = "asc", align = "left"),
    Assault = reactable::colDef(name = "Assaults", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Assault), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "gold")}),
    Rape = reactable::colDef(name = "Rapes", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Rape), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "orange")}),
    Murder = reactable::colDef(name = "Murders", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Murder), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "red")})
    ))

htmltools::div(
  class = "drug-mapping-data",
  htmltools::div(class = "drug-mapping-data-header",
                 htmltools::div(
                   class = "drug-mapping-data-title",
                   "Source: OMOP2OBO v1.0 - OMOP v5.3 Drug Exposure Ingredient Mappings"),
                 paste("Last Update: ", run_time, " EST", sep = "")),
  table
)
```


### Measurement Mappings

```{r table3}

table <- reactable::reactable(
  data = data,
  pagination = FALSE,
  highlight = TRUE,
  height = 1200,
  defaultSorted = "States",
  sortable = TRUE,
  borderless = TRUE,
  defaultPageSize = nrow(data),
  columns = list(
    States = reactable::colDef(name = "States", sortable = TRUE, defaultSortOrder = "asc", align = "left"),
    Assault = reactable::colDef(name = "Assaults", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Assault), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "gold")}),
    Rape = reactable::colDef(name = "Rapes", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Rape), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "orange")}),
    Murder = reactable::colDef(name = "Murders", sortable = TRUE, align = "left",
                                cell = function(value) {
                                width <- paste0(value * 100 / max(data$Murder), "%")
                                value <- format(value, big.mark = ",")
                                bar_chart(value, width = width, fill = "red")})
    ))

htmltools::div(
  class = "lab-mapping-data",
  htmltools::div(class = "lab-mapping-data-header",
                 htmltools::div(
                   class = "lab-mapping-data-title",
                   "Source: OMOP2OBO v1.0 - OMOP v5.3 Measurement Mappings"),
                 paste("Last Update: ", run_time, " EST", sep = "")),
  table
)
```



About {data-icon="fa-address-card"}
===================================== 

**The OMOP2OBO Mapping Dashboard**

The US Wildfire Dashboard provides a live update for the ongoing wildfire in the US. This dashboard is built with R using [Rmakrdown](https://rmarkdown.rstudio.com/) and [flexdashboard](https://rmarkdown.rstudio.com/flexdashboard/) framework, and can easily reproduce by others. The code behind the dashboard available [here](https://github.com/RamiKrispin/uswildfire)


**Mapping Overview**

Add some example here of a mapping

**OMOP2OBO Users and Usecases**  




___

We’d love to hear from you! To get in touch with us, please join or start a new [discussion](https://github.com/callahantiff/OMOP2OBO_Dashboard/discussions), create an [issue](https://github.com/callahantiff/OMOP2OBO_Dashboard/issues) or send us an [email](https://mail.google.com/mail/u/0/?view=cm&fs=1&tf=1&to=callahantiff@gmail.com) 💌